Using OLR
vclust <- varclus (~angle+brick+wood+mixed+ density+EN +TC + TC_mature_soil + TC_saprolite_soil + TC_weath_rock + TC_unstable_structure + T_construction + spring + landfill + garbage + crack + leaning_wall + scars + downward_floor + tilted + fracture + conc_rainfall + wastewater + leak + septic_tank + tree + ground_veg + deforestation + banana + drainage , data=train.data)
# took out density since training has 0 d4 and it was not allowing do the plot
p <- plot(vclust)
par(mfrow=c(6,5))
plot.xmean.ordinaly (risk~angle+brick+wood+mixed+ density+EN +TC + TC_mature_soil + TC_saprolite_soil + TC_weath_rock + TC_unstable_structure + T_construction + spring + landfill + garbage + crack + leaning_wall + scars + downward_floor + tilted + fracture + conc_rainfall + wastewater + leak + septic_tank + tree + ground_veg + deforestation + banana + drainage, data=train.data, cr=TRUE , subn=FALSE)
#angle + building+density+EN +TC + TC_mature_Soil + TC_saprolito + TC_weath_rock + TC_rock + TC_geol_desfav + Taterro + DepEncNatural + DepTaludeAterro + DepTaludeCorte + DepTaludeAterro + aterro + lixo + entulho + crack + belly_wall + scars + drawback + tilted + fracture + conc_rainfall_water + wastewater + leak + septic_tank + drainage + tree + ground_veg + deforestation + banana
Diagnostic 2: Proportion (-5% of one of the parameters based on what is expected. Since some parameters have 2 predictors, others 5)
#library(plyr)
brick <- count(train.data$brick) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "brick")
wood <- count(train.data$wood) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "wood")
mixed <- count(train.data$mixed) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "mixed")
TC_mature_soil <- count(train.data$TC_mature_soil) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "TC_mature_soil")
T_construction <- count(train.data$T_construction ) %>%
mutate ("Percentage"=(freq/265)*100) %>%
mutate("Classifier" = "T_construction ")
spring <- count(train.data$spring) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "spring")
landfill <- count(train.data$landfill) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "landfill")
garbage <- count(train.data$garbage) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "garbage")
crack <- count(train.data$crack) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "crack")
leaning_wall <- count(train.data$leaning_wall) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "leaning_wall")
scars <- count(train.data$scars) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "DepTaludeAterro")
downward_floor <- count(train.data$downward_floor) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "scars")
tilted <- count(train.data$tilted) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "tilted")
conc_rainfall <- count(train.data$conc_rainfall) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "conc_rainfall")
wastewater <- count(train.data$wastewater) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "wastewater")
leak <- count(train.data$leak) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "conc_rainfall_water")
septic_tank <- count(train.data$septic_tank) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "septic_tank")
angle <- count(train.data$angle) # angle A less than 5% but the rest are okay (3,50, 91, 277, 109) Expected=106
angle <- angle %>%
mutate("Percentage"=(freq/106)*100)%>%
mutate("Classifier" = "angle")
EN <- count(train.data$EN) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "EN")
TC <- count(train.data$TC) %>%
mutate ("Percentage"=(freq/265)*100) %>%
mutate("Classifier" = "TC")
TC_saprolite_soil <- count(train.data$TC_saprolite_soil ) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "TC_saprolite_soil ")
banana <- count(train.data$banana) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "banana")
drainage <- count(train.data$drainage) %>%
mutate ("Percentage"=(freq/176.7)*100)%>%
mutate("Classifier" = "drainage")
deforestation <- count(train.data$deforestation) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "deforestation")
TC_unstable_structure <- count(train.data$TC_unstable_structure ) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "TC_unstable_structure ")
tree <- count(train.data$tree) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "tree")
ground_veg <- count(train.data$ground_veg) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "ground_veg")
density <- count(train.data$density) %>% #(79, 415, 36) # d4 =0
mutate ("Percentage"=(freq/132.5)*100)%>%
mutate("Classifier" = "density")
TC_weath_rock <- count(train.data$TC_weath_rock ) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "TC_weath_rock ")
fracture <- count(train.data$fracture) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "fracture")
df <- rbind(brick, wood, mixed, TC_mature_soil, T_construction, spring, landfill, garbage, crack, leaning_wall, scars, downward_floor, tilted, conc_rainfall, wastewater, leak, septic_tank, angle, EN, TC, TC_saprolite_soil, banana, drainage, deforestation, TC_unstable_structure, tree, ground_veg,density, TC_weath_rock, fracture)
df
## x freq Percentage Classifier
## 1 FALSE 35 13.2075472 brick
## 2 TRUE 495 186.7924528 brick
## 3 FALSE 458 172.8301887 wood
## 4 TRUE 72 27.1698113 wood
## 5 FALSE 489 184.5283019 mixed
## 6 TRUE 41 15.4716981 mixed
## 7 FALSE 244 92.0754717 TC_mature_soil
## 8 TRUE 286 107.9245283 TC_mature_soil
## 9 FALSE 197 74.3396226 T_construction
## 10 TRUE 333 125.6603774 T_construction
## 11 FALSE 515 194.3396226 spring
## 12 TRUE 15 5.6603774 spring
## 13 FALSE 326 123.0188679 landfill
## 14 TRUE 204 76.9811321 landfill
## 15 FALSE 332 125.2830189 garbage
## 16 TRUE 198 74.7169811 garbage
## 17 FALSE 439 165.6603774 crack
## 18 TRUE 91 34.3396226 crack
## 19 FALSE 503 189.8113208 leaning_wall
## 20 TRUE 27 10.1886792 leaning_wall
## 21 FALSE 321 121.1320755 DepTaludeAterro
## 22 TRUE 209 78.8679245 DepTaludeAterro
## 23 FALSE 470 177.3584906 scars
## 24 TRUE 60 22.6415094 scars
## 25 FALSE 429 161.8867925 tilted
## 26 TRUE 101 38.1132075 tilted
## 27 FALSE 17 6.4150943 conc_rainfall
## 28 TRUE 513 193.5849057 conc_rainfall
## 29 FALSE 210 79.2452830 wastewater
## 30 TRUE 320 120.7547170 wastewater
## 31 FALSE 348 131.3207547 conc_rainfall_water
## 32 TRUE 182 68.6792453 conc_rainfall_water
## 33 FALSE 525 198.1132075 septic_tank
## 34 TRUE 5 1.8867925 septic_tank
## 35 C 34 32.0754717 angle
## 36 D 120 113.2075472 angle
## 37 E 376 354.7169811 angle
## 38 FALSE 346 130.5660377 EN
## 39 TRUE 184 69.4339623 EN
## 40 FALSE 25 9.4339623 TC
## 41 TRUE 505 190.5660377 TC
## 42 FALSE 445 167.9245283 TC_saprolite_soil
## 43 TRUE 85 32.0754717 TC_saprolite_soil
## 44 FALSE 359 135.4716981 banana
## 45 TRUE 171 64.5283019 banana
## 46 Y 66 37.3514431 drainage
## 47 P 235 132.9937748 drainage
## 48 N 229 129.5981890 drainage
## 49 FALSE 492 185.6603774 deforestation
## 50 TRUE 38 14.3396226 deforestation
## 51 FALSE 513 193.5849057 TC_unstable_structure
## 52 TRUE 17 6.4150943 TC_unstable_structure
## 53 FALSE 215 81.1320755 tree
## 54 TRUE 315 118.8679245 tree
## 55 FALSE 163 61.5094340 ground_veg
## 56 TRUE 367 138.4905660 ground_veg
## 57 d1 58 43.7735849 density
## 58 d2 441 332.8301887 density
## 59 d3 31 23.3962264 density
## 60 FALSE 520 196.2264151 TC_weath_rock
## 61 TRUE 10 3.7735849 TC_weath_rock
## 62 FALSE 529 199.6226415 fracture
## 63 TRUE 1 0.3773585 fracture
TC_weath_rock, TC_rock_TC_geol_desf, fracture, TC_rock
f1 <- lrm(risk ~ building + EN + TC_saprolito + Taterro + DepEncNatural + DepTaludeAterro + DepTaludeCorte + landfill + garbage + construction_deposit + crack + leaning_wall + scars + downward_floor +tilted + conc_rainfall_water + wastewater + leak + tree + ground_veg + banana , data=train.data, x=TRUE , y=TRUE)
f1 <- lrm(risk ~ building + EN + TC_saprolito + Taterro + DepEncNatural + DepTaludeAterro + DepTaludeCorte + landfill + garbage + construction_deposit + crack + leaning_wall + scars + downward_floor +tilted + conc_rainfall_water + wastewater + leak + tree + ground_veg + banana + septic_tank +TC_mature_Soil , data=train.data, x=TRUE , y=TRUE) print (f1 , latex =TRUE , coefs =5) stargazer(anova(f1), type=“text”, style=“default”)
# Equation 1
eq_OLR_01 <- polr(risk ~ brick+ wood+ EN + TC_mature_soil + T_construction + spring+ landfill+ leak+ garbage+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ septic_tank+ conc_rainfall+ wastewater+ ground_veg + angle + TC_saprolite_soil, data= train.data
, method = "logistic", Hess = TRUE)
ctable <- coef(summary(eq_OLR_01))
p<- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE*2) #computes p value
ctable <- cbind(ctable, "p value" = p )
ctable
## Value Std. Error t value p value
## brickTRUE -1.2390663 0.4613852 -2.6855353 3.620686e-03
## woodTRUE 1.0071461 0.3268982 3.0809164 1.031823e-03
## ENTRUE 0.4768801 0.3580960 1.3317103 9.147770e-02
## TC_mature_soilTRUE 0.5497335 0.2233394 2.4614271 6.919276e-03
## T_constructionTRUE 0.3108695 0.3708859 0.8381810 2.009645e-01
## springTRUE -0.5769465 0.6805492 -0.8477660 1.982841e-01
## landfillTRUE 0.4254165 0.3278022 1.2977843 9.718073e-02
## leakTRUE -0.3205059 0.2427776 -1.3201628 9.339033e-02
## garbageTRUE 0.2616029 0.2924380 0.8945586 1.855116e-01
## crackTRUE 1.6927245 0.3261907 5.1893704 1.055032e-07
## leaning_wallTRUE 1.5950203 0.5392333 2.9579409 1.548507e-03
## scarsTRUE 4.1897938 0.3788602 11.0589441 9.920981e-29
## downward_floorTRUE 1.1338038 0.3748885 3.0243762 1.245732e-03
## tiltedTRUE 0.9646526 0.3135689 3.0763657 1.047703e-03
## septic_tankTRUE 0.4330775 1.0461477 0.4139736 3.394467e-01
## conc_rainfallTRUE 1.6363234 0.5570323 2.9375735 1.653959e-03
## wastewaterTRUE 0.9372871 0.2440191 3.8410392 6.125728e-05
## ground_vegTRUE 0.8658041 0.2583794 3.3509023 4.027435e-04
## angleD 0.7153446 0.4670190 1.5317249 6.279517e-02
## angleE 0.6761471 0.5288539 1.2785139 1.005341e-01
## TC_saprolite_soilTRUE 0.1763019 0.2933702 0.6009537 2.739354e-01
## R1|R2 0.6364662 0.8916385 0.7138164 2.376703e-01
## R2|R3 5.0268331 0.9458544 5.3145951 5.344736e-08
## R3|R4 10.3248355 1.0610976 9.7303351 1.119271e-22
stargazer((ctable), type="text", style="default", digits = 2)
##
## ======================================================
## Value Std. Error t value p value
## ------------------------------------------------------
## brickTRUE -1.24 0.46 -2.69 0.004
## woodTRUE 1.01 0.33 3.08 0.001
## ENTRUE 0.48 0.36 1.33 0.09
## TC_mature_soilTRUE 0.55 0.22 2.46 0.01
## T_constructionTRUE 0.31 0.37 0.84 0.20
## springTRUE -0.58 0.68 -0.85 0.20
## landfillTRUE 0.43 0.33 1.30 0.10
## leakTRUE -0.32 0.24 -1.32 0.09
## garbageTRUE 0.26 0.29 0.89 0.19
## crackTRUE 1.69 0.33 5.19 0.0000
## leaning_wallTRUE 1.60 0.54 2.96 0.002
## scarsTRUE 4.19 0.38 11.06 0
## downward_floorTRUE 1.13 0.37 3.02 0.001
## tiltedTRUE 0.96 0.31 3.08 0.001
## septic_tankTRUE 0.43 1.05 0.41 0.34
## conc_rainfallTRUE 1.64 0.56 2.94 0.002
## wastewaterTRUE 0.94 0.24 3.84 0.0001
## ground_vegTRUE 0.87 0.26 3.35 0.0004
## angleD 0.72 0.47 1.53 0.06
## angleE 0.68 0.53 1.28 0.10
## TC_saprolite_soilTRUE 0.18 0.29 0.60 0.27
## R1| R2 0.64 0.89 0.71 0.24
## R2| R3 5.03 0.95 5.31 0.0000
## R3| R4 10.32 1.06 9.73 0
## ------------------------------------------------------
less p-value = 0.10 (TC_saprolitoTRUE,TaterroTRUE, DepTaludeAterroTRUE,DepTaludeAterroTRUE,landfillTRUE, construction_depositTRUE, leakTRUE)
par(mfrow=c(5,4))
plot.xmean.ordinaly (risk~ brick+ wood+ EN + TC_mature_soil + T_construction + spring+ landfill+ leak+ garbage+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ septic_tank+ conc_rainfall+ wastewater+ ground_veg + angle + TC_saprolite_soil
,data=train.data, cr=TRUE , subn=FALSE , cex.lab=1.5, cex.axis=2, cex.sub=2, cex.main=2)
Equation 1
sf <- function (y) {
c('y>=1' = qlogis(mean(y>=1)),
'y>=2' = qlogis(mean(y>=2)),
'y>=3' = qlogis(mean(y>=3)),
'y>=4' = qlogis(mean(y>=4)))
}
s<-with(train.data, summary(as.numeric(risk)~brick+ wood+ EN + TC_mature_soil + T_construction + spring+ landfill+ leak+ garbage+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ septic_tank+ conc_rainfall+ wastewater+ ground_veg + angle + TC_saprolite_soil
, fun=sf))
s
## as.numeric(risk) N= 529 , 1 Missing
##
## +-----------------+---+---+----+----------+------------+----------+
## | | |N |y>=1|y>=2 |y>=3 |y>=4 |
## +-----------------+---+---+----+----------+------------+----------+
## |brick |No | 35|Inf | 3.5263605| 1.575536361|-0.5260931|
## | |Yes|494|Inf | 2.2761518|-0.097242548|-2.0771662|
## +-----------------+---+---+----+----------+------------+----------+
## |wood |No |457|Inf | 2.2392580|-0.153473402|-2.2143609|
## | |Yes| 72|Inf | 3.1354942| 1.025852934|-0.7563261|
## +-----------------+---+---+----+----------+------------+----------+
## |EN |No |345|Inf | 1.9229206|-0.417557154|-2.3884464|
## | |Yes|184|Inf | 4.0998847| 0.801135819|-1.3131721|
## +-----------------+---+---+----+----------+------------+----------+
## |TC_mature_soil |No |244|Inf | 1.8908504|-0.263814591|-2.2155737|
## | |Yes|285|Inf | 2.8903718| 0.218407947|-1.7006073|
## +-----------------+---+---+----+----------+------------+----------+
## |T_construction |No |197|Inf | 1.4978854|-0.999521386|-4.1692459|
## | |Yes|332|Inf | 3.3735459| 0.556067588|-1.4128614|
## +-----------------+---+---+----+----------+------------+----------+
## |spring |No |514|Inf | 2.2961817|-0.023347364|-2.0237526|
## | |Yes| 15|Inf | Inf| 0.693147181| 0.1335314|
## +-----------------+---+---+----+----------+------------+----------+
## |landfill |No |325|Inf | 1.8281271|-0.522329448|-2.8364760|
## | |Yes|204|Inf | 4.6151205| 0.851970766|-1.1249296|
## +-----------------+---+---+----+----------+------------+----------+
## |leak |No |347|Inf | 1.9826422|-0.296092551|-2.4329866|
## | |Yes|182|Inf | 3.5667118| 0.563935449|-1.2669476|
## +-----------------+---+---+----+----------+------------+----------+
## |garbage |No |332|Inf | 2.0166110|-0.328216256|-2.5978471|
## | |Yes|197|Inf | 3.1623055| 0.551647618|-1.2172180|
## +-----------------+---+---+----+----------+------------+----------+
## |crack |No |438|Inf | 2.1671471|-0.350579054|-2.7227563|
## | |Yes| 91|Inf | 3.7954892| 2.339399066|-0.1984509|
## +-----------------+---+---+----+----------+------------+----------+
## |leaning_wall |No |502|Inf | 2.2701498|-0.087705580|-2.1367310|
## | |Yes| 27|Inf | Inf| 2.079441542| 0.2231436|
## +-----------------+---+---+----+----------+------------+----------+
## |scars |No |320|Inf | 1.7844867|-1.445954198|-4.3694479|
## | |Yes|209|Inf | 5.3375381| 3.521446510|-0.8178507|
## +-----------------+---+---+----+----------+------------+----------+
## |downward_floor |No |469|Inf | 2.1948577|-0.244277863|-2.2187308|
## | |Yes| 60|Inf | Inf| 3.367295830|-0.5465437|
## +-----------------+---+---+----+----------+------------+----------+
## |tilted |No |428|Inf | 2.1167792|-0.417161148|-2.3877429|
## | |Yes|101|Inf | 4.6051702| 2.597384633|-0.7683706|
## +-----------------+---+---+----+----------+------------+----------+
## |septic_tank |No |524|Inf | 2.3173689|-0.007633625|-1.9372144|
## | |Yes| 5|Inf | Inf| 0.405465108|-0.4054651|
## +-----------------+---+---+----+----------+------------+----------+
## |conc_rainfall |No | 17|Inf |-0.3566749|-2.772588722| -Inf|
## | |Yes|512|Inf | 2.5523969| 0.054701136|-1.8763169|
## +-----------------+---+---+----+----------+------------+----------+
## |wastewater |No |210|Inf | 1.6094379|-0.465363250|-2.8954096|
## | |Yes|319|Inf | 3.2419411| 0.296831267|-1.5252932|
## +-----------------+---+---+----+----------+------------+----------+
## |ground_veg |No |163|Inf | 1.3710269|-1.371026889|-2.8397280|
## | |Yes|366|Inf | 3.2245738| 0.537142932|-1.6493103|
## +-----------------+---+---+----+----------+------------+----------+
## |angle |C | 34|Inf | Inf|-0.356674944|-3.4965076|
## | |D |120|Inf | 3.3672958| 0.927986772|-1.1895841|
## | |E |375|Inf | 2.0439349|-0.251991706|-2.1535495|
## +-----------------+---+---+----+----------+------------+----------+
## |TC_saprolite_soil|No |444|Inf | 2.2072749|-0.099180320|-2.0419840|
## | |Yes| 85|Inf | 3.3081070| 0.504556011|-1.3862944|
## +-----------------+---+---+----+----------+------------+----------+
## |Overall | |529|Inf | 2.3277965|-0.003780723|-1.9138903|
## +-----------------+---+---+----+----------+------------+----------+
plot(s, which=1:4, pch=1:4, xlab='logit', main=' ', xlim=c(-5,5), cex.lab=1, cex.axis=1, cex.sub=1)
f2 <- lrm(risk ~ angle + building + EN + TC_saprolito + Taterro + DepEncNatural + DepTaludeAterro + DepTaludeCorte + landfill + garbage + construction_deposit + crack + leaning_wall + scars + downward_floor +tilted + conc_rainfall_water + wastewater + leak + drainage + TC_mature_Soil + density + TC + tree +ground_veg + deforestation + banana , data=train.data, x=TRUE , y=TRUE)
stargazer(anova(f2), type="text", style="default")
eq_OLR_02 <- polr(risk ~ brick+ wood+ EN+ TC_mature_soil+ T_construction+ landfill+ leak+ garbage+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ mixed+ conc_rainfall+ wastewater+ angle+ banana+ drainage+ TC_saprolite_soil+ TC+ deforestation,
data= train.data
, method = "logistic", Hess = TRUE)
ctable <- coef(summary(eq_OLR_02))
p<- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE*2) #computes p value
ctable <- cbind(ctable, "p value" = p )
ctable
## Value Std. Error t value p value
## brickTRUE -0.43428225 0.5593616 -0.77638912 2.187596e-01
## woodTRUE 1.04338525 0.3433839 3.03853867 1.188643e-03
## ENTRUE 0.37273983 0.3754420 0.99280259 1.604031e-01
## TC_mature_soilTRUE 0.41053323 0.2347865 1.74853843 4.018542e-02
## T_constructionTRUE 0.28973309 0.3787010 0.76507091 2.221147e-01
## landfillTRUE 0.39820802 0.3322528 1.19850927 1.153594e-01
## leakTRUE -0.57100241 0.2537036 -2.25066774 1.220329e-02
## garbageTRUE 0.25513343 0.2997366 0.85119219 1.973313e-01
## crackTRUE 1.68182586 0.3277933 5.13075137 1.442939e-07
## leaning_wallTRUE 1.56025982 0.5474243 2.85018351 2.184701e-03
## treeTRUE 0.03627160 0.2519211 0.14398001 4.427581e-01
## downward_floorTRUE 1.07810669 0.3741172 2.88173493 1.977461e-03
## tiltedTRUE 0.84540446 0.3096889 2.72985046 3.168153e-03
## ground_vegTRUE 0.69300097 0.2794987 2.47944255 6.579396e-03
## scarsTRUE 4.25531841 0.3852020 11.04697933 1.133577e-28
## mixedTRUE 1.25057841 0.5460390 2.29027304 1.100275e-02
## conc_rainfallTRUE 1.17599861 0.5896631 1.99435681 2.305654e-02
## wastewaterTRUE 0.81730759 0.2492762 3.27872279 5.213901e-04
## angleD 0.60703651 0.4741130 1.28036264 1.002088e-01
## angleE 0.56304223 0.5362091 1.05004232 1.468493e-01
## bananaTRUE 0.32908163 0.2557007 1.28697958 9.905070e-02
## drainage.L 0.93233807 0.2825364 3.29988604 4.836205e-04
## drainage.Q -0.17788229 0.1915268 -0.92875938 1.765069e-01
## TC_saprolite_soilTRUE 0.15475905 0.3015818 0.51315786 3.039205e-01
## TCTRUE -0.03809614 0.5491873 -0.06936821 4.723483e-01
## deforestationTRUE 0.06286918 0.4133030 0.15211405 4.395485e-01
## R1|R2 0.66626825 1.1321921 0.58847630 2.781063e-01
## R2|R3 5.28878615 1.1727555 4.50970926 3.245827e-06
## R3|R4 10.61787605 1.2762388 8.31966224 4.410717e-17
stargazer((ctable), type="text", style="default", digits=2)
##
## ======================================================
## Value Std. Error t value p value
## ------------------------------------------------------
## brickTRUE -0.43 0.56 -0.78 0.22
## woodTRUE 1.04 0.34 3.04 0.001
## ENTRUE 0.37 0.38 0.99 0.16
## TC_mature_soilTRUE 0.41 0.23 1.75 0.04
## T_constructionTRUE 0.29 0.38 0.77 0.22
## landfillTRUE 0.40 0.33 1.20 0.12
## leakTRUE -0.57 0.25 -2.25 0.01
## garbageTRUE 0.26 0.30 0.85 0.20
## crackTRUE 1.68 0.33 5.13 0.0000
## leaning_wallTRUE 1.56 0.55 2.85 0.002
## treeTRUE 0.04 0.25 0.14 0.44
## downward_floorTRUE 1.08 0.37 2.88 0.002
## tiltedTRUE 0.85 0.31 2.73 0.003
## ground_vegTRUE 0.69 0.28 2.48 0.01
## scarsTRUE 4.26 0.39 11.05 0
## mixedTRUE 1.25 0.55 2.29 0.01
## conc_rainfallTRUE 1.18 0.59 1.99 0.02
## wastewaterTRUE 0.82 0.25 3.28 0.001
## angleD 0.61 0.47 1.28 0.10
## angleE 0.56 0.54 1.05 0.15
## bananaTRUE 0.33 0.26 1.29 0.10
## drainage.L 0.93 0.28 3.30 0.0005
## drainage.Q -0.18 0.19 -0.93 0.18
## TC_saprolite_soilTRUE 0.15 0.30 0.51 0.30
## TCTRUE -0.04 0.55 -0.07 0.47
## deforestationTRUE 0.06 0.41 0.15 0.44
## R1| R2 0.67 1.13 0.59 0.28
## R2| R3 5.29 1.17 4.51 0.0000
## R3| R4 10.62 1.28 8.32 0
## ------------------------------------------------------
par(mfrow=c(6,4))
plot.xmean.ordinaly (risk~ brick+ wood+ EN+ TC_mature_soil+ T_construction+ landfill+ leak+ garbage+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ mixed+ conc_rainfall+ wastewater+ angle+ banana+ drainage+ TC_saprolite_soil+ TC+ deforestation
,data=train.data, cr=TRUE , subn=FALSE , cex.lab=1.5, cex.axis=4, cex.sub=4, cex.main=4)
sf <- function (y) {
c('y>=1' = qlogis(mean(y>=1)),
'y>=2' = qlogis(mean(y>=2)),
'y>=3' = qlogis(mean(y>=3)),
'y>=4' = qlogis(mean(y>=4)))
}
s<-with(train.data, summary(as.numeric(risk)~brick+ wood+ EN+ TC_mature_soil+ T_construction+ landfill+ leak+ garbage+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ mixed+ conc_rainfall+ wastewater+ angle+ banana+ drainage+ TC_saprolite_soil+ TC+ deforestation,data=train.data
, fun=sf))
s
## as.numeric(risk) N= 529 , 1 Missing
##
## +-----------------+---+---+----+----------+------------+----------+
## | | |N |y>=1|y>=2 |y>=3 |y>=4 |
## +-----------------+---+---+----+----------+------------+----------+
## |brick |No | 35|Inf | 3.5263605| 1.575536361|-0.5260931|
## | |Yes|494|Inf | 2.2761518|-0.097242548|-2.0771662|
## +-----------------+---+---+----+----------+------------+----------+
## |wood |No |457|Inf | 2.2392580|-0.153473402|-2.2143609|
## | |Yes| 72|Inf | 3.1354942| 1.025852934|-0.7563261|
## +-----------------+---+---+----+----------+------------+----------+
## |EN |No |345|Inf | 1.9229206|-0.417557154|-2.3884464|
## | |Yes|184|Inf | 4.0998847| 0.801135819|-1.3131721|
## +-----------------+---+---+----+----------+------------+----------+
## |TC_mature_soil |No |244|Inf | 1.8908504|-0.263814591|-2.2155737|
## | |Yes|285|Inf | 2.8903718| 0.218407947|-1.7006073|
## +-----------------+---+---+----+----------+------------+----------+
## |T_construction |No |197|Inf | 1.4978854|-0.999521386|-4.1692459|
## | |Yes|332|Inf | 3.3735459| 0.556067588|-1.4128614|
## +-----------------+---+---+----+----------+------------+----------+
## |landfill |No |325|Inf | 1.8281271|-0.522329448|-2.8364760|
## | |Yes|204|Inf | 4.6151205| 0.851970766|-1.1249296|
## +-----------------+---+---+----+----------+------------+----------+
## |leak |No |347|Inf | 1.9826422|-0.296092551|-2.4329866|
## | |Yes|182|Inf | 3.5667118| 0.563935449|-1.2669476|
## +-----------------+---+---+----+----------+------------+----------+
## |garbage |No |332|Inf | 2.0166110|-0.328216256|-2.5978471|
## | |Yes|197|Inf | 3.1623055| 0.551647618|-1.2172180|
## +-----------------+---+---+----+----------+------------+----------+
## |crack |No |438|Inf | 2.1671471|-0.350579054|-2.7227563|
## | |Yes| 91|Inf | 3.7954892| 2.339399066|-0.1984509|
## +-----------------+---+---+----+----------+------------+----------+
## |leaning_wall |No |502|Inf | 2.2701498|-0.087705580|-2.1367310|
## | |Yes| 27|Inf | Inf| 2.079441542| 0.2231436|
## +-----------------+---+---+----+----------+------------+----------+
## |tree |No |214|Inf | 1.6320377|-0.679160939|-2.3285606|
## | |Yes|315|Inf | 3.2288262| 0.445311017|-1.6916760|
## +-----------------+---+---+----+----------+------------+----------+
## |downward_floor |No |469|Inf | 2.1948577|-0.244277863|-2.2187308|
## | |Yes| 60|Inf | Inf| 3.367295830|-0.5465437|
## +-----------------+---+---+----+----------+------------+----------+
## |tilted |No |428|Inf | 2.1167792|-0.417161148|-2.3877429|
## | |Yes|101|Inf | 4.6051702| 2.597384633|-0.7683706|
## +-----------------+---+---+----+----------+------------+----------+
## |ground_veg |No |163|Inf | 1.3710269|-1.371026889|-2.8397280|
## | |Yes|366|Inf | 3.2245738| 0.537142932|-1.6493103|
## +-----------------+---+---+----+----------+------------+----------+
## |scars |No |320|Inf | 1.7844867|-1.445954198|-4.3694479|
## | |Yes|209|Inf | 5.3375381| 3.521446510|-0.8178507|
## +-----------------+---+---+----+----------+------------+----------+
## |mixed |No |488|Inf | 2.2626685|-0.073803975|-2.0634045|
## | |Yes| 41|Inf | 3.6888795| 0.882389180|-0.7672552|
## +-----------------+---+---+----+----------+------------+----------+
## |conc_rainfall |No | 17|Inf |-0.3566749|-2.772588722| -Inf|
## | |Yes|512|Inf | 2.5523969| 0.054701136|-1.8763169|
## +-----------------+---+---+----+----------+------------+----------+
## |wastewater |No |210|Inf | 1.6094379|-0.465363250|-2.8954096|
## | |Yes|319|Inf | 3.2419411| 0.296831267|-1.5252932|
## +-----------------+---+---+----+----------+------------+----------+
## |angle |C | 34|Inf | Inf|-0.356674944|-3.4965076|
## | |D |120|Inf | 3.3672958| 0.927986772|-1.1895841|
## | |E |375|Inf | 2.0439349|-0.251991706|-2.1535495|
## +-----------------+---+---+----+----------+------------+----------+
## |banana |No |358|Inf | 1.9395407|-0.372979653|-2.2543830|
## | |Yes|171|Inf | 4.4367515| 0.800392711|-1.3936204|
## +-----------------+---+---+----+----------+------------+----------+
## |drainage |Y | 66|Inf | 0.6931472|-1.609437912|-3.4657359|
## | |P |234|Inf | 2.3167697|-0.561295049|-2.4849066|
## | |N |229|Inf | 4.0298060| 1.013090115|-1.3272960|
## +-----------------+---+---+----+----------+------------+----------+
## |TC_saprolite_soil|No |444|Inf | 2.2072749|-0.099180320|-2.0419840|
## | |Yes| 85|Inf | 3.3081070| 0.504556011|-1.3862944|
## +-----------------+---+---+----+----------+------------+----------+
## |TC |No | 25|Inf | Inf| 0.753771802|-0.9444616|
## | |Yes|504|Inf | 2.2745358|-0.039687748|-1.9826959|
## +-----------------+---+---+----+----------+------------+----------+
## |deforestation |No |491|Inf | 2.3956755| 0.061118815|-1.8800521|
## | |Yes| 38|Inf | 1.6739764|-0.897941593|-2.4567358|
## +-----------------+---+---+----+----------+------------+----------+
## |Overall | |529|Inf | 2.3277965|-0.003780723|-1.9138903|
## +-----------------+---+---+----+----------+------------+----------+
plot(s, which=1:4, pch=1:4, xlab='logit', main=' ', xlim=c(-5,5), cex.lab=1, cex.axis=2, cex.sub=1)
f3 <- lrm(risk ~ angle +building + EN + DepTaludeAterro+ DepTaludeCorte+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ conc_rainfall_water+ wastewater+ tree + TC , data=train.data, x=TRUE , y=TRUE) stargazer(anova(f3), type=“text”, style=“default”)
# x=TRUE, y=TRUE used by resid() below
eq_OLR_03 <- polr(risk ~ wood+ TC_mature_soil+ T_construction+ landfill+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana+ drainage, data=train.data
, method = "logistic", Hess = TRUE)
ctable <- coef(summary(eq_OLR_03))
p<- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE*2) #computes p value
ctable <- cbind(ctable, "p value" = p )
ctable
## Value Std. Error t value p value
## woodTRUE 0.92006523 0.3197546 2.87741061 2.004767e-03
## TC_mature_soilTRUE 0.45476338 0.2233160 2.03641183 2.085451e-02
## T_constructionTRUE 0.50821156 0.3044479 1.66928933 4.753003e-02
## landfillTRUE 0.23117883 0.2942678 0.78560699 2.160489e-01
## crackTRUE 1.77452208 0.3160897 5.61398266 9.886102e-09
## leaning_wallTRUE 1.60809991 0.5337990 3.01255707 1.295284e-03
## treeTRUE 0.01050506 0.2421647 0.04337981 4.826994e-01
## downward_floorTRUE 0.99400266 0.3562622 2.79008705 2.634694e-03
## tiltedTRUE 0.89463608 0.3059645 2.92398606 1.727901e-03
## ground_vegTRUE 0.67421846 0.2709742 2.48812827 6.420870e-03
## scarsTRUE 4.08532113 0.3755368 10.87861752 7.287838e-28
## conc_rainfallTRUE 1.13427719 0.5786522 1.96020527 2.498590e-02
## wastewaterTRUE 0.81342603 0.2408353 3.37752024 3.657129e-04
## bananaTRUE 0.40211950 0.2449944 1.64134146 5.036328e-02
## drainage.L 0.92255583 0.2762185 3.33994886 4.189691e-04
## drainage.Q -0.15615152 0.1872207 -0.83405033 2.021263e-01
## R1|R2 0.56123565 0.5638092 0.99543544 1.597623e-01
## R2|R3 5.04303382 0.6305953 7.99725900 6.360972e-16
## R3|R4 10.21538351 0.7847474 13.01741689 4.870535e-39
stargazer((ctable), type="text", style="default", digits = 2)
##
## ===================================================
## Value Std. Error t value p value
## ---------------------------------------------------
## woodTRUE 0.92 0.32 2.88 0.002
## TC_mature_soilTRUE 0.45 0.22 2.04 0.02
## T_constructionTRUE 0.51 0.30 1.67 0.05
## landfillTRUE 0.23 0.29 0.79 0.22
## crackTRUE 1.77 0.32 5.61 0
## leaning_wallTRUE 1.61 0.53 3.01 0.001
## treeTRUE 0.01 0.24 0.04 0.48
## downward_floorTRUE 0.99 0.36 2.79 0.003
## tiltedTRUE 0.89 0.31 2.92 0.002
## ground_vegTRUE 0.67 0.27 2.49 0.01
## scarsTRUE 4.09 0.38 10.88 0
## conc_rainfallTRUE 1.13 0.58 1.96 0.02
## wastewaterTRUE 0.81 0.24 3.38 0.0004
## bananaTRUE 0.40 0.24 1.64 0.05
## drainage.L 0.92 0.28 3.34 0.0004
## drainage.Q -0.16 0.19 -0.83 0.20
## R1| R2 0.56 0.56 1.00 0.16
## R2| R3 5.04 0.63 8.00 0
## R3| R4 10.22 0.78 13.02 0
## ---------------------------------------------------
#print (f3 , latex =TRUE , coefs =5)
par(mfrow=c(3,5))
plot.xmean.ordinaly (risk ~ wood+ TC_mature_soil+ T_construction+ landfill+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana+ drainage,,
data=train.data, cr=TRUE , subn=FALSE , cex.points =0.65)
sf <- function (y) {
c('y>=1' = qlogis(mean(y>=1)),
'y>=2' = qlogis(mean(y>=2)),
'y>=3' = qlogis(mean(y>=3)),
'y>=4' = qlogis(mean(y>=4)))
}
s<-with(train.data, summary(as.numeric(risk)~wood+ TC_mature_soil+ T_construction+ landfill+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana+ drainage, fun=sf))
s
## as.numeric(risk) N= 529 , 1 Missing
##
## +--------------+---+---+----+----------+------------+----------+
## | | |N |y>=1|y>=2 |y>=3 |y>=4 |
## +--------------+---+---+----+----------+------------+----------+
## |wood |No |457|Inf | 2.2392580|-0.153473402|-2.2143609|
## | |Yes| 72|Inf | 3.1354942| 1.025852934|-0.7563261|
## +--------------+---+---+----+----------+------------+----------+
## |TC_mature_soil|No |244|Inf | 1.8908504|-0.263814591|-2.2155737|
## | |Yes|285|Inf | 2.8903718| 0.218407947|-1.7006073|
## +--------------+---+---+----+----------+------------+----------+
## |T_construction|No |197|Inf | 1.4978854|-0.999521386|-4.1692459|
## | |Yes|332|Inf | 3.3735459| 0.556067588|-1.4128614|
## +--------------+---+---+----+----------+------------+----------+
## |landfill |No |325|Inf | 1.8281271|-0.522329448|-2.8364760|
## | |Yes|204|Inf | 4.6151205| 0.851970766|-1.1249296|
## +--------------+---+---+----+----------+------------+----------+
## |crack |No |438|Inf | 2.1671471|-0.350579054|-2.7227563|
## | |Yes| 91|Inf | 3.7954892| 2.339399066|-0.1984509|
## +--------------+---+---+----+----------+------------+----------+
## |leaning_wall |No |502|Inf | 2.2701498|-0.087705580|-2.1367310|
## | |Yes| 27|Inf | Inf| 2.079441542| 0.2231436|
## +--------------+---+---+----+----------+------------+----------+
## |tree |No |214|Inf | 1.6320377|-0.679160939|-2.3285606|
## | |Yes|315|Inf | 3.2288262| 0.445311017|-1.6916760|
## +--------------+---+---+----+----------+------------+----------+
## |downward_floor|No |469|Inf | 2.1948577|-0.244277863|-2.2187308|
## | |Yes| 60|Inf | Inf| 3.367295830|-0.5465437|
## +--------------+---+---+----+----------+------------+----------+
## |tilted |No |428|Inf | 2.1167792|-0.417161148|-2.3877429|
## | |Yes|101|Inf | 4.6051702| 2.597384633|-0.7683706|
## +--------------+---+---+----+----------+------------+----------+
## |ground_veg |No |163|Inf | 1.3710269|-1.371026889|-2.8397280|
## | |Yes|366|Inf | 3.2245738| 0.537142932|-1.6493103|
## +--------------+---+---+----+----------+------------+----------+
## |scars |No |320|Inf | 1.7844867|-1.445954198|-4.3694479|
## | |Yes|209|Inf | 5.3375381| 3.521446510|-0.8178507|
## +--------------+---+---+----+----------+------------+----------+
## |conc_rainfall |No | 17|Inf |-0.3566749|-2.772588722| -Inf|
## | |Yes|512|Inf | 2.5523969| 0.054701136|-1.8763169|
## +--------------+---+---+----+----------+------------+----------+
## |wastewater |No |210|Inf | 1.6094379|-0.465363250|-2.8954096|
## | |Yes|319|Inf | 3.2419411| 0.296831267|-1.5252932|
## +--------------+---+---+----+----------+------------+----------+
## |banana |No |358|Inf | 1.9395407|-0.372979653|-2.2543830|
## | |Yes|171|Inf | 4.4367515| 0.800392711|-1.3936204|
## +--------------+---+---+----+----------+------------+----------+
## |drainage |Y | 66|Inf | 0.6931472|-1.609437912|-3.4657359|
## | |P |234|Inf | 2.3167697|-0.561295049|-2.4849066|
## | |N |229|Inf | 4.0298060| 1.013090115|-1.3272960|
## +--------------+---+---+----+----------+------------+----------+
## |Overall | |529|Inf | 2.3277965|-0.003780723|-1.9138903|
## +--------------+---+---+----+----------+------------+----------+
plot(s, which=1:4, pch=1:4, xlab='logit', main=' ', xlim=c(-5,5), cex.lab=0.6, cex.axis=0.6, cex.sub=0.6)
f4 <- lrm(risk ~ building + EN
+ DepEncNatural
+ crack + leaning_wall + scars + downward_floor +tilted + conc_rainfall_water + wastewater + drainage + TC_mature_Soil + TC + +ground_veg
,data=train.data, x=TRUE , y=TRUE) # x=TRUE, y=TRUE used by resid() below #print (f4 , latex =TRUE , coefs =5) stargazer(anova(f4), type=“text”, style=“default”)
eq_OLR_04 <- polr(risk~ wood+ TC_mature_soil+ T_construction+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana+ drainage
, data= train.data
, method = "logistic", Hess = TRUE)
p<- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE*2) #computes p value
ctable <- coef(summary(eq_OLR_04))
ctable <- cbind(ctable, "p value" = p )
## Warning in cbind(ctable, `p value` = p): number of rows of result is not a
## multiple of vector length (arg 2)
ctable
## Value Std. Error t value p value
## woodTRUE 0.921222085 0.3191972 2.8860593 2.004767e-03
## TC_mature_soilTRUE 0.428153341 0.2205185 1.9415758 2.085451e-02
## T_constructionTRUE 0.647898991 0.2473875 2.6189644 4.753003e-02
## crackTRUE 1.807450123 0.3138113 5.7596724 2.160489e-01
## leaning_wallTRUE 1.581723953 0.5348641 2.9572444 9.886102e-09
## treeTRUE -0.006649604 0.2409958 -0.0275922 1.295284e-03
## downward_floorTRUE 1.023142282 0.3537082 2.8926165 4.826994e-01
## tiltedTRUE 0.940526352 0.3004566 3.1303238 2.634694e-03
## ground_vegTRUE 0.698257501 0.2689098 2.5966231 1.727901e-03
## scarsTRUE 4.079253951 0.3755660 10.8616156 6.420870e-03
## conc_rainfallTRUE 1.154871595 0.5785593 1.9961163 7.287838e-28
## wastewaterTRUE 0.777188288 0.2363234 3.2886642 2.498590e-02
## bananaTRUE 0.403632707 0.2448098 1.6487603 3.657129e-04
## drainage.L 0.929176173 0.2757864 3.3691884 5.036328e-02
## drainage.Q -0.146797771 0.1866843 -0.7863422 4.189691e-04
## R1|R2 0.564567379 0.5644160 1.0002681 2.021263e-01
## R2|R3 5.048387656 0.6313539 7.9961302 1.597623e-01
## R3|R4 10.213125790 0.7854888 13.0022555 6.360972e-16
stargazer((ctable), type="text", style="default", digits=2)
##
## ===================================================
## Value Std. Error t value p value
## ---------------------------------------------------
## woodTRUE 0.92 0.32 2.89 0.002
## TC_mature_soilTRUE 0.43 0.22 1.94 0.02
## T_constructionTRUE 0.65 0.25 2.62 0.05
## crackTRUE 1.81 0.31 5.76 0.22
## leaning_wallTRUE 1.58 0.53 2.96 0
## treeTRUE -0.01 0.24 -0.03 0.001
## downward_floorTRUE 1.02 0.35 2.89 0.48
## tiltedTRUE 0.94 0.30 3.13 0.003
## ground_vegTRUE 0.70 0.27 2.60 0.002
## scarsTRUE 4.08 0.38 10.86 0.01
## conc_rainfallTRUE 1.15 0.58 2.00 0
## wastewaterTRUE 0.78 0.24 3.29 0.02
## bananaTRUE 0.40 0.24 1.65 0.0004
## drainage.L 0.93 0.28 3.37 0.05
## drainage.Q -0.15 0.19 -0.79 0.0004
## R1| R2 0.56 0.56 1.00 0.20
## R2| R3 5.05 0.63 8.00 0.16
## R3| R4 10.21 0.79 13.00 0
## ---------------------------------------------------
par(mfrow=c(4,4))
plot.xmean.ordinaly (risk ~ wood+ TC_mature_soil+ T_construction+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana+ drainage
,data=train.data, cr=TRUE , subn=FALSE , cex.points =0.65)
sf <- function (y) {
c('y>=1' = qlogis(mean(y>=1)),
'y>=2' = qlogis(mean(y>=2)),
'y>=3' = qlogis(mean(y>=3)),
'y>=4' = qlogis(mean(y>=4)))
}
s<-with(train.data, summary(as.numeric(risk)~wood+ TC_mature_soil+ T_construction+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana+ drainage
, fun=sf))
s
## as.numeric(risk) N= 529 , 1 Missing
##
## +--------------+---+---+----+----------+------------+----------+
## | | |N |y>=1|y>=2 |y>=3 |y>=4 |
## +--------------+---+---+----+----------+------------+----------+
## |wood |No |457|Inf | 2.2392580|-0.153473402|-2.2143609|
## | |Yes| 72|Inf | 3.1354942| 1.025852934|-0.7563261|
## +--------------+---+---+----+----------+------------+----------+
## |TC_mature_soil|No |244|Inf | 1.8908504|-0.263814591|-2.2155737|
## | |Yes|285|Inf | 2.8903718| 0.218407947|-1.7006073|
## +--------------+---+---+----+----------+------------+----------+
## |T_construction|No |197|Inf | 1.4978854|-0.999521386|-4.1692459|
## | |Yes|332|Inf | 3.3735459| 0.556067588|-1.4128614|
## +--------------+---+---+----+----------+------------+----------+
## |crack |No |438|Inf | 2.1671471|-0.350579054|-2.7227563|
## | |Yes| 91|Inf | 3.7954892| 2.339399066|-0.1984509|
## +--------------+---+---+----+----------+------------+----------+
## |leaning_wall |No |502|Inf | 2.2701498|-0.087705580|-2.1367310|
## | |Yes| 27|Inf | Inf| 2.079441542| 0.2231436|
## +--------------+---+---+----+----------+------------+----------+
## |tree |No |214|Inf | 1.6320377|-0.679160939|-2.3285606|
## | |Yes|315|Inf | 3.2288262| 0.445311017|-1.6916760|
## +--------------+---+---+----+----------+------------+----------+
## |downward_floor|No |469|Inf | 2.1948577|-0.244277863|-2.2187308|
## | |Yes| 60|Inf | Inf| 3.367295830|-0.5465437|
## +--------------+---+---+----+----------+------------+----------+
## |tilted |No |428|Inf | 2.1167792|-0.417161148|-2.3877429|
## | |Yes|101|Inf | 4.6051702| 2.597384633|-0.7683706|
## +--------------+---+---+----+----------+------------+----------+
## |ground_veg |No |163|Inf | 1.3710269|-1.371026889|-2.8397280|
## | |Yes|366|Inf | 3.2245738| 0.537142932|-1.6493103|
## +--------------+---+---+----+----------+------------+----------+
## |scars |No |320|Inf | 1.7844867|-1.445954198|-4.3694479|
## | |Yes|209|Inf | 5.3375381| 3.521446510|-0.8178507|
## +--------------+---+---+----+----------+------------+----------+
## |conc_rainfall |No | 17|Inf |-0.3566749|-2.772588722| -Inf|
## | |Yes|512|Inf | 2.5523969| 0.054701136|-1.8763169|
## +--------------+---+---+----+----------+------------+----------+
## |wastewater |No |210|Inf | 1.6094379|-0.465363250|-2.8954096|
## | |Yes|319|Inf | 3.2419411| 0.296831267|-1.5252932|
## +--------------+---+---+----+----------+------------+----------+
## |banana |No |358|Inf | 1.9395407|-0.372979653|-2.2543830|
## | |Yes|171|Inf | 4.4367515| 0.800392711|-1.3936204|
## +--------------+---+---+----+----------+------------+----------+
## |drainage |Y | 66|Inf | 0.6931472|-1.609437912|-3.4657359|
## | |P |234|Inf | 2.3167697|-0.561295049|-2.4849066|
## | |N |229|Inf | 4.0298060| 1.013090115|-1.3272960|
## +--------------+---+---+----+----------+------------+----------+
## |Overall | |529|Inf | 2.3277965|-0.003780723|-1.9138903|
## +--------------+---+---+----+----------+------------+----------+
plot(s, which=1:4, pch=1:4, xlab='logit', main=' ', xlim=c(-5,5), cex.lab=0.7, cex.axis=0.5, cex.sub=0.5)
# x=TRUE, y=TRUE used by resid() below
#print (f1 , latex =TRUE , coefs =5)
#stargazer(anova(f1), type="text", style="default")
eq_OLR_05 <- polr(risk ~ brick+ wood+ TC_mature_soil+ T_construction+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ conc_rainfall+ wastewater+ ground_veg, data= train.data
, method = "logistic", Hess = TRUE)
ctable <- coef(summary(eq_OLR_05))
p<- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE*2) #computes p value
ctable <- cbind(ctable, "p value" = p )
ctable
## Value Std. Error t value p value
## brickTRUE -0.9677011 0.4453529 -2.1728862 1.489444e-02
## woodTRUE 0.9704591 0.3200049 3.0326383 1.212130e-03
## TC_mature_soilTRUE 0.4772300 0.2167449 2.2018051 1.383954e-02
## T_constructionTRUE 0.7131302 0.2431542 2.9328319 1.679429e-03
## crackTRUE 1.7828386 0.3119006 5.7160474 5.451518e-09
## leaning_wallTRUE 1.5082465 0.5321385 2.8343119 2.296224e-03
## scarsTRUE 4.1687751 0.3758985 11.0901606 7.001804e-29
## downward_floorTRUE 1.0886868 0.3589116 3.0333005 1.209473e-03
## tiltedTRUE 1.0468586 0.3022256 3.4638314 2.662701e-04
## conc_rainfallTRUE 1.6315823 0.5489943 2.9719474 1.479587e-03
## wastewaterTRUE 0.8695603 0.2328380 3.7346150 9.400128e-05
## ground_vegTRUE 0.9239225 0.2438946 3.7882043 7.587004e-05
## R1|R2 0.2211011 0.6945791 0.3183239 3.751196e-01
## R2|R3 4.5360526 0.7547378 6.0101036 9.270241e-10
## R3|R4 9.7274016 0.8723667 11.1505879 3.556742e-29
stargazer((ctable), type="text", style="default", digits = 2)
##
## ===================================================
## Value Std. Error t value p value
## ---------------------------------------------------
## brickTRUE -0.97 0.45 -2.17 0.01
## woodTRUE 0.97 0.32 3.03 0.001
## TC_mature_soilTRUE 0.48 0.22 2.20 0.01
## T_constructionTRUE 0.71 0.24 2.93 0.002
## crackTRUE 1.78 0.31 5.72 0
## leaning_wallTRUE 1.51 0.53 2.83 0.002
## scarsTRUE 4.17 0.38 11.09 0
## downward_floorTRUE 1.09 0.36 3.03 0.001
## tiltedTRUE 1.05 0.30 3.46 0.0003
## conc_rainfallTRUE 1.63 0.55 2.97 0.001
## wastewaterTRUE 0.87 0.23 3.73 0.0001
## ground_vegTRUE 0.92 0.24 3.79 0.0001
## R1| R2 0.22 0.69 0.32 0.38
## R2| R3 4.54 0.75 6.01 0
## R3| R4 9.73 0.87 11.15 0
## ---------------------------------------------------
par(mfrow=c(3,4))
plot.xmean.ordinaly (risk ~ brick+ wood+ TC_mature_soil+ T_construction+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ conc_rainfall+ wastewater+ ground_veg
,data=train.data, cr=TRUE , subn=FALSE , cex.points =0.65)
sf <- function (y) {
c('y>=1' = qlogis(mean(y>=1)),
'y>=2' = qlogis(mean(y>=2)),
'y>=3' = qlogis(mean(y>=3)),
'y>=4' = qlogis(mean(y>=4)))
}
s<-with(train.data, summary(as.numeric(risk)~brick+ wood+ TC_mature_soil+ T_construction+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ conc_rainfall+ wastewater+ ground_veg
, fun=sf))
s
## as.numeric(risk) N= 529 , 1 Missing
##
## +--------------+---+---+----+----------+------------+----------+
## | | |N |y>=1|y>=2 |y>=3 |y>=4 |
## +--------------+---+---+----+----------+------------+----------+
## |brick |No | 35|Inf | 3.5263605| 1.575536361|-0.5260931|
## | |Yes|494|Inf | 2.2761518|-0.097242548|-2.0771662|
## +--------------+---+---+----+----------+------------+----------+
## |wood |No |457|Inf | 2.2392580|-0.153473402|-2.2143609|
## | |Yes| 72|Inf | 3.1354942| 1.025852934|-0.7563261|
## +--------------+---+---+----+----------+------------+----------+
## |TC_mature_soil|No |244|Inf | 1.8908504|-0.263814591|-2.2155737|
## | |Yes|285|Inf | 2.8903718| 0.218407947|-1.7006073|
## +--------------+---+---+----+----------+------------+----------+
## |T_construction|No |197|Inf | 1.4978854|-0.999521386|-4.1692459|
## | |Yes|332|Inf | 3.3735459| 0.556067588|-1.4128614|
## +--------------+---+---+----+----------+------------+----------+
## |crack |No |438|Inf | 2.1671471|-0.350579054|-2.7227563|
## | |Yes| 91|Inf | 3.7954892| 2.339399066|-0.1984509|
## +--------------+---+---+----+----------+------------+----------+
## |leaning_wall |No |502|Inf | 2.2701498|-0.087705580|-2.1367310|
## | |Yes| 27|Inf | Inf| 2.079441542| 0.2231436|
## +--------------+---+---+----+----------+------------+----------+
## |scars |No |320|Inf | 1.7844867|-1.445954198|-4.3694479|
## | |Yes|209|Inf | 5.3375381| 3.521446510|-0.8178507|
## +--------------+---+---+----+----------+------------+----------+
## |downward_floor|No |469|Inf | 2.1948577|-0.244277863|-2.2187308|
## | |Yes| 60|Inf | Inf| 3.367295830|-0.5465437|
## +--------------+---+---+----+----------+------------+----------+
## |tilted |No |428|Inf | 2.1167792|-0.417161148|-2.3877429|
## | |Yes|101|Inf | 4.6051702| 2.597384633|-0.7683706|
## +--------------+---+---+----+----------+------------+----------+
## |conc_rainfall |No | 17|Inf |-0.3566749|-2.772588722| -Inf|
## | |Yes|512|Inf | 2.5523969| 0.054701136|-1.8763169|
## +--------------+---+---+----+----------+------------+----------+
## |wastewater |No |210|Inf | 1.6094379|-0.465363250|-2.8954096|
## | |Yes|319|Inf | 3.2419411| 0.296831267|-1.5252932|
## +--------------+---+---+----+----------+------------+----------+
## |ground_veg |No |163|Inf | 1.3710269|-1.371026889|-2.8397280|
## | |Yes|366|Inf | 3.2245738| 0.537142932|-1.6493103|
## +--------------+---+---+----+----------+------------+----------+
## |Overall | |529|Inf | 2.3277965|-0.003780723|-1.9138903|
## +--------------+---+---+----+----------+------------+----------+
plot(s, which=1:4, pch=1:4, xlab='logit', main=' ', xlim=c(-5,5), cex.lab=0.7, cex.axis=0.5, cex.sub=0.5)
# x=TRUE, y=TRUE used by resid() below
#print (f1 , latex =TRUE , coefs =5)
#stargazer(anova(f1), type="text", style="default")
eq_OLR_06 <- polr(risk ~ brick+ wood+ mixed+ EN+ TC+ T_construction+ landfill+ leak+ garbage+ crack+ leaning_wall+ tree+ tilted+ angle+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana, data= train.data
, method = "logistic", Hess = TRUE)
ctable <- coef(summary(eq_OLR_06))
p<- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE*2) #computes p value
ctable <- cbind(ctable, "p value" = p )
ctable
## Value Std. Error t value p value
## brickTRUE -0.5569510 0.5614827 -0.9919289 1.606161e-01
## woodTRUE 1.0447383 0.3295202 3.1704833 7.609278e-04
## mixedTRUE 1.3828298 0.5386066 2.5674206 5.122913e-03
## ENTRUE 0.4487755 0.3679583 1.2196368 1.113013e-01
## TCTRUE 0.2091751 0.5128117 0.4078985 3.416741e-01
## T_constructionTRUE 0.3348989 0.3633389 0.9217260 1.783358e-01
## landfillTRUE 0.4388227 0.3203354 1.3698853 8.536136e-02
## leakTRUE -0.3058842 0.2409840 -1.2693134 1.021647e-01
## garbageTRUE 0.2263916 0.2903523 0.7797136 2.177798e-01
## crackTRUE 1.6181105 0.3213096 5.0359857 2.376981e-07
## leaning_wallTRUE 1.6621309 0.5554303 2.9925103 1.383467e-03
## treeTRUE 0.1005813 0.2430887 0.4137636 3.395236e-01
## tiltedTRUE 1.0306191 0.3044894 3.3847453 3.562216e-04
## angleD 0.7516338 0.4634524 1.6218145 5.242153e-02
## angleE 0.7410218 0.5235041 1.4155034 7.846048e-02
## ground_vegTRUE 0.8095937 0.2703781 2.9943018 1.375368e-03
## scarsTRUE 4.3254013 0.3832016 11.2875330 7.561079e-30
## conc_rainfallTRUE 1.8157617 0.5561365 3.2649568 5.474039e-04
## wastewaterTRUE 0.8607088 0.2387776 3.6046466 1.562890e-04
## bananaTRUE 0.4112325 0.2495966 1.6475882 4.971861e-02
## R1|R2 1.5769252 1.0892900 1.4476634 7.385561e-02
## R2|R3 5.9303038 1.1436474 5.1854301 1.077584e-07
## R3|R4 11.1837127 1.2529802 8.9256902 2.214642e-19
stargazer((ctable), type="text", style="default", digits = 2)
##
## ===================================================
## Value Std. Error t value p value
## ---------------------------------------------------
## brickTRUE -0.56 0.56 -0.99 0.16
## woodTRUE 1.04 0.33 3.17 0.001
## mixedTRUE 1.38 0.54 2.57 0.01
## ENTRUE 0.45 0.37 1.22 0.11
## TCTRUE 0.21 0.51 0.41 0.34
## T_constructionTRUE 0.33 0.36 0.92 0.18
## landfillTRUE 0.44 0.32 1.37 0.09
## leakTRUE -0.31 0.24 -1.27 0.10
## garbageTRUE 0.23 0.29 0.78 0.22
## crackTRUE 1.62 0.32 5.04 0.0000
## leaning_wallTRUE 1.66 0.56 2.99 0.001
## treeTRUE 0.10 0.24 0.41 0.34
## tiltedTRUE 1.03 0.30 3.38 0.0004
## angleD 0.75 0.46 1.62 0.05
## angleE 0.74 0.52 1.42 0.08
## ground_vegTRUE 0.81 0.27 2.99 0.001
## scarsTRUE 4.33 0.38 11.29 0
## conc_rainfallTRUE 1.82 0.56 3.26 0.001
## wastewaterTRUE 0.86 0.24 3.60 0.0002
## bananaTRUE 0.41 0.25 1.65 0.05
## R1| R2 1.58 1.09 1.45 0.07
## R2| R3 5.93 1.14 5.19 0.0000
## R3| R4 11.18 1.25 8.93 0
## ---------------------------------------------------
par(mfrow=c(5,4))
plot.xmean.ordinaly (risk ~ brick+ wood+ mixed+ EN+ TC+ T_construction+ landfill+ leak+ garbage+ crack+ leaning_wall+ tree+ tilted+ angle+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana
,data=train.data, cr=TRUE , subn=FALSE , cex.points =0.65)
sf <- function (y) {
c('y>=1' = qlogis(mean(y>=1)),
'y>=2' = qlogis(mean(y>=2)),
'y>=3' = qlogis(mean(y>=3)),
'y>=4' = qlogis(mean(y>=4)))
}
s<-with(train.data, summary(as.numeric(risk)~brick+ wood+ mixed+ EN+ TC+ T_construction+ landfill+ leak+ garbage+ crack+ leaning_wall+ tree+ tilted+ angle+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana
, fun=sf))
s
## as.numeric(risk) N= 529 , 1 Missing
##
## +--------------+---+---+----+----------+------------+----------+
## | | |N |y>=1|y>=2 |y>=3 |y>=4 |
## +--------------+---+---+----+----------+------------+----------+
## |brick |No | 35|Inf | 3.5263605| 1.575536361|-0.5260931|
## | |Yes|494|Inf | 2.2761518|-0.097242548|-2.0771662|
## +--------------+---+---+----+----------+------------+----------+
## |wood |No |457|Inf | 2.2392580|-0.153473402|-2.2143609|
## | |Yes| 72|Inf | 3.1354942| 1.025852934|-0.7563261|
## +--------------+---+---+----+----------+------------+----------+
## |mixed |No |488|Inf | 2.2626685|-0.073803975|-2.0634045|
## | |Yes| 41|Inf | 3.6888795| 0.882389180|-0.7672552|
## +--------------+---+---+----+----------+------------+----------+
## |EN |No |345|Inf | 1.9229206|-0.417557154|-2.3884464|
## | |Yes|184|Inf | 4.0998847| 0.801135819|-1.3131721|
## +--------------+---+---+----+----------+------------+----------+
## |TC |No | 25|Inf | Inf| 0.753771802|-0.9444616|
## | |Yes|504|Inf | 2.2745358|-0.039687748|-1.9826959|
## +--------------+---+---+----+----------+------------+----------+
## |T_construction|No |197|Inf | 1.4978854|-0.999521386|-4.1692459|
## | |Yes|332|Inf | 3.3735459| 0.556067588|-1.4128614|
## +--------------+---+---+----+----------+------------+----------+
## |landfill |No |325|Inf | 1.8281271|-0.522329448|-2.8364760|
## | |Yes|204|Inf | 4.6151205| 0.851970766|-1.1249296|
## +--------------+---+---+----+----------+------------+----------+
## |leak |No |347|Inf | 1.9826422|-0.296092551|-2.4329866|
## | |Yes|182|Inf | 3.5667118| 0.563935449|-1.2669476|
## +--------------+---+---+----+----------+------------+----------+
## |garbage |No |332|Inf | 2.0166110|-0.328216256|-2.5978471|
## | |Yes|197|Inf | 3.1623055| 0.551647618|-1.2172180|
## +--------------+---+---+----+----------+------------+----------+
## |crack |No |438|Inf | 2.1671471|-0.350579054|-2.7227563|
## | |Yes| 91|Inf | 3.7954892| 2.339399066|-0.1984509|
## +--------------+---+---+----+----------+------------+----------+
## |leaning_wall |No |502|Inf | 2.2701498|-0.087705580|-2.1367310|
## | |Yes| 27|Inf | Inf| 2.079441542| 0.2231436|
## +--------------+---+---+----+----------+------------+----------+
## |tree |No |214|Inf | 1.6320377|-0.679160939|-2.3285606|
## | |Yes|315|Inf | 3.2288262| 0.445311017|-1.6916760|
## +--------------+---+---+----+----------+------------+----------+
## |tilted |No |428|Inf | 2.1167792|-0.417161148|-2.3877429|
## | |Yes|101|Inf | 4.6051702| 2.597384633|-0.7683706|
## +--------------+---+---+----+----------+------------+----------+
## |angle |C | 34|Inf | Inf|-0.356674944|-3.4965076|
## | |D |120|Inf | 3.3672958| 0.927986772|-1.1895841|
## | |E |375|Inf | 2.0439349|-0.251991706|-2.1535495|
## +--------------+---+---+----+----------+------------+----------+
## |ground_veg |No |163|Inf | 1.3710269|-1.371026889|-2.8397280|
## | |Yes|366|Inf | 3.2245738| 0.537142932|-1.6493103|
## +--------------+---+---+----+----------+------------+----------+
## |scars |No |320|Inf | 1.7844867|-1.445954198|-4.3694479|
## | |Yes|209|Inf | 5.3375381| 3.521446510|-0.8178507|
## +--------------+---+---+----+----------+------------+----------+
## |conc_rainfall |No | 17|Inf |-0.3566749|-2.772588722| -Inf|
## | |Yes|512|Inf | 2.5523969| 0.054701136|-1.8763169|
## +--------------+---+---+----+----------+------------+----------+
## |wastewater |No |210|Inf | 1.6094379|-0.465363250|-2.8954096|
## | |Yes|319|Inf | 3.2419411| 0.296831267|-1.5252932|
## +--------------+---+---+----+----------+------------+----------+
## |banana |No |358|Inf | 1.9395407|-0.372979653|-2.2543830|
## | |Yes|171|Inf | 4.4367515| 0.800392711|-1.3936204|
## +--------------+---+---+----+----------+------------+----------+
## |Overall | |529|Inf | 2.3277965|-0.003780723|-1.9138903|
## +--------------+---+---+----+----------+------------+----------+
plot(s, which=1:4, pch=1:4, xlab='logit', main=' ', xlim=c(-5,5), cex.lab=0.7, cex.axis=0.5, cex.sub=0.5)
predictedLevel1 <- predict(eq_OLR_01, test.data) # predict the levels directly
predictedScores1 <- predict(eq_OLR_01, test.data, type="p")
# predict the probabilites
## Confusion matrix and misclassification error
table(test.data$risk, predictedLevel1)
## predictedLevel1
## R1 R2 R3 R4
## R1 4 15 0 0
## R2 3 83 7 0
## R3 0 21 55 8
## R4 0 1 13 14
p1 <- mean(as.character(test.data$risk) != as.character(predictedLevel1)) #misclassification error
p1
## [1] 0.3035714
predictedLevel2 <- predict(eq_OLR_02, test.data) # predict the levels directly
## Confusion matrix and misclassification error
table(test.data$risk, predictedLevel2)
## predictedLevel2
## R1 R2 R3 R4
## R1 4 15 0 0
## R2 5 81 7 0
## R3 0 22 52 10
## R4 0 1 13 14
p2 <- mean(as.character(test.data$risk) != as.character(predictedLevel2))
p2
## [1] 0.3258929
predictedLevel3 <- predict(eq_OLR_03, test.data) # predict the levels directly
predictedScores1 <- predict(eq_OLR_03, test.data, type="p")
# predict the probabilites
## Confusion matrix and misclassification error
table(test.data$risk, predictedLevel3)
## predictedLevel3
## R1 R2 R3 R4
## R1 4 15 0 0
## R2 5 82 6 0
## R3 0 23 52 9
## R4 0 1 14 13
p3 <- mean(as.character(test.data$risk) != as.character(predictedLevel3))
p3
## [1] 0.3258929
predictedLevel4 <- predict(eq_OLR_04, test.data) # predict the levels directly
predictedScores1 <- predict(eq_OLR_04, test.data, type="p")
# predict the probabilites
## Confusion matrix and misclassification error
table(test.data$risk, predictedLevel4)
## predictedLevel4
## R1 R2 R3 R4
## R1 4 15 0 0
## R2 5 82 6 0
## R3 0 23 52 9
## R4 0 1 14 13
p4 <- mean(as.character(test.data$risk) != as.character(predictedLevel4))
p4
## [1] 0.3258929
predictedLevel5 <- predict(eq_OLR_05, test.data) # predict the levels directly
predictedScores5 <- predict(eq_OLR_05, test.data, type="p")
# predict the probabilites
## Confusion matrix and misclassification error
table(test.data$risk, predictedLevel5)
## predictedLevel5
## R1 R2 R3 R4
## R1 4 15 0 0
## R2 2 84 7 0
## R3 0 20 56 8
## R4 0 1 13 14
p5 <- mean(as.character(test.data$risk) != as.character(predictedLevel5))
p5
## [1] 0.2946429
predictedLevel6 <- predict(eq_OLR_06, test.data) # predict the levels directly
predictedScores6 <- predict(eq_OLR_06, test.data, type="p")
# predict the probabilites
## Confusion matrix and misclassification error
table(test.data$risk, predictedLevel6)
## predictedLevel6
## R1 R2 R3 R4
## R1 4 15 0 0
## R2 0 86 7 0
## R3 0 21 54 9
## R4 0 1 15 12
p6 <- mean(as.character(test.data$risk) != as.character(predictedLevel6))
p6
## [1] 0.3035714
#Table
df2 <- data.frame(
"Equations"=c(1:6),
"Predicted"=c(1-p1,
1-p2,
1-p3,
1-p4,
1-p5,
1-p6
)
)
df2
## Equations Predicted
## 1 1 0.6964286
## 2 2 0.6741071
## 3 3 0.6741071
## 4 4 0.6741071
## 5 5 0.7053571
## 6 6 0.6964286